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Expectations over Unspoken Alternatives Predict Pragmatic Inferences.

, , , и . CoRR, (2023)

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Другие публикации лиц с тем же именем

Speakers optimize information density through syntactic reduction, и . Advances in Neural Information Processing Systems 19, MIT Press, Cambridge, MA, (2007)Eye movement evidence that readers maintain and act on uncertainty about past linguistic input, , , и . Proceedings of the National Academy of Sciences, 106 (50): 21086-21090 (декабря 2009)Language Learning and Processing in People and Machines., , и . NAACL-HLT (Tutorial Abstracts), стр. 19-21. Association for Computational Linguistics, (2019)Noisy-context surprisal as a human sentence processing cost model., и . EACL (1), стр. 688-698. Association for Computational Linguistics, (2017)Data-driven learning of symbolic constraints for a log-linear model in a phonological setting., и . COLING, стр. 2217-2226. ACL, (2016)A Noisy-Channel Model of Human Sentence Comprehension under Uncertain Input.. EMNLP, стр. 234-243. ACL, (2008)Investigating Novel Verb Learning in BERT: Selectional Preference Classes and Alternation-Based Syntactic Generalization., , и . BlackboxNLP@EMNLP, стр. 265-275. Association for Computational Linguistics, (2020)Automated Whole Sentence Grammar Correction Using a Noisy Channel Model., и . ACL, стр. 934-944. The Association for Computer Linguistics, (2011)Expectations over Unspoken Alternatives Predict Pragmatic Inferences., , , и . CoRR, (2023)Structure-sensitive Noise Inference: Comprehenders Expect Exchange Errors., и . CogSci, cognitivesciencesociety.org, (2016)